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Mathematical Programming Models for Environmental Quality Control

Author

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  • Harvey J. Greenberg

    (University of Colorado at Denver, Denver, Colorado)

Abstract

This paper surveys the use of mathematical programming models for controlling environmental quality. The scope includes air, water, and land quality, stemming from the first works in the 1960s. It also includes integrated models, generally that are economic equilibrium models which have an equivalent mathematical program or use mathematical programming to compute a fixed point. A primary goal of this survey is to identify interesting research avenues for people in mathematical programming with an interest in applying it to help control our environment with as little economic sacrifice as possible.

Suggested Citation

  • Harvey J. Greenberg, 1995. "Mathematical Programming Models for Environmental Quality Control," Operations Research, INFORMS, vol. 43(4), pages 578-622, August.
    • Handle: RePEc:inm:oropre:v:43:y:1995:i:4:p:578-622
    DOI: 10.1287/opre.43.4.578
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    Citations

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    Cited by:

    1. Krupnick, Alan & Shih, Jhih-Shyang & Bergin, S. & Russell, Armistead, 2003. "Controlling Ozone and Fine Particulates: Cost Benefit Analysis with Meteorological Variability," RFF Working Paper Series dp-03-55, Resources for the Future.
    2. Chialin Chen, 2001. "Design for the Environment: A Quality-Based Model for Green Product Development," Management Science, INFORMS, vol. 47(2), pages 250-263, February.
    3. Cooper, W. W. & Hemphill, H. & Huang, Z. & Li, S. & Lelas, V. & Sullivan, D. W., 1997. "Survey of mathematical programming models in air pollution management," European Journal of Operational Research, Elsevier, vol. 96(1), pages 1-35, January.
    4. Daniel, S. E. & Diakoulaki, D. C. & Pappis, C. P., 1997. "Operations research and environmental planning," European Journal of Operational Research, Elsevier, vol. 102(2), pages 248-263, October.
    5. Julie Ann Stuart & Jane C. Ammons & Laura J. Turbini, 1999. "A Product and Process Selection Model with Multidisciplinary Environmental Considerations," Operations Research, INFORMS, vol. 47(2), pages 221-234, April.
    6. Makowski, Marek, 2005. "A structured modeling technology," European Journal of Operational Research, Elsevier, vol. 166(3), pages 615-648, November.
    7. Pinto, F.S. & Figueira, J.R. & Marques, R.C., 2015. "A multi-objective approach with soft constraints for water supply and wastewater coverage improvements," European Journal of Operational Research, Elsevier, vol. 246(2), pages 609-618.
    8. Ben Sadiki & Fabien Ilunga & Michel Shengo, 2023. "Dispersal Mechanisms of Trace Metal Elements in the Environment: The Case of Mineral Wastes Stored in Tshamilemba District of the City of Lubumbashi, DR Congo," Sustainability, MDPI, vol. 15(5), pages 1-18, March.
    9. Cynthia Hardy & Vikram Bhakoo & Steve Maguire, 2020. "A New Methodology for Supply Chain Management: Discourse Analysis and its Potential for Theoretical Advancement," Journal of Supply Chain Management, Institute for Supply Management, vol. 56(2), pages 19-35, April.
    10. Kumar Rajaram & Charles J. Corbett, 2002. "Achieving Environmental and Productivity Improvements Through Model-Based Process Redesign," Operations Research, INFORMS, vol. 50(5), pages 751-763, October.
    11. Rajesh, R., 2020. "Sustainable supply chains in the Indian context: An integrative decision-making model," Technology in Society, Elsevier, vol. 61(C).
    12. Tang, Christopher S. & Zhou, Sean, 2012. "Research advances in environmentally and socially sustainable operations," European Journal of Operational Research, Elsevier, vol. 223(3), pages 585-594.

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